fix: update unit tests

deepmodeling · Jan 29, 2024 · d3090b9 · d3090b9
1 parent a08092c
commit d3090b9
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Showing 2 changed files with 69 additions and 4 deletions.
diff --git a/deepmd/utils/pair_tab.py b/deepmd/utils/pair_tab.py
@@ -127,7 +127,7 @@ def _check_table_upper_boundary(self) -> None:
                 self.vdata = np.concatenate((self.vdata, pad_zero), axis=0)
         else:
             # if table values do not decay to `0` at rcut
-            if self.rcut <= self.rmax:
+            if self.rcut < self.rmax:
                 logging.warning(
                     "The energy provided in the table does not decay to 0 at rcut."
                 )

diff --git a/source/tests/test_pairtab_preprocess.py b/source/tests/test_pairtab_preprocess.py
@@ -24,7 +24,7 @@ def setUp(self, mock_loadtxt) -> None:
             ]
         )
 
-        self.tab1 = PairTab(filename=file_path, rcut=0.01)
+        self.tab1 = PairTab(filename=file_path, rcut=0.028)
         self.tab2 = PairTab(filename=file_path, rcut=0.02)
         self.tab3 = PairTab(filename=file_path, rcut=0.022)
         self.tab4 = PairTab(filename=file_path, rcut=0.03)
@@ -38,6 +38,8 @@ def test_preprocess(self):
                     [0.01, 0.8, 1.6, 2.4],
                     [0.015, 0.5, 1.0, 1.5],
                     [0.02, 0.25, 0.4, 0.75],
+                [0.025, 0.0, 0.0, 0.0],
+                [0.03, 0., 0., 0.],
                 ]
             ),
         )
@@ -49,6 +51,7 @@ def test_preprocess(self):
                     [0.01, 0.8, 1.6, 2.4],
                     [0.015, 0.5, 1.0, 1.5],
                     [0.02, 0.25, 0.4, 0.75],
+                [0.025, 0.,   0.,  0.],
                 ]
             ),
         )
@@ -145,5 +148,67 @@ def test_preprocess(self):
 
         # for this test case, padding zeros between 0.025 and 0.03 will cause the cubic spline go below zero and result in negative energy values,
         # we will do post process to overwrite spline coefficient `a3`,`a2`,`a1`,`a0`, to ensure energy decays to `0`.
-        temp_data = self.tab3.tab_data.reshape(2, 2, -1, 4)
-        np.testing.assert_allclose(temp_data[:, :, -1, :], np.zeros((2, 2, 4)))
+        temp_data = self.tab3.tab_data.reshape(2,2,-1,4)
+        np.testing.assert_allclose(temp_data[:,:,-1,:], np.zeros((2,2,4)))
+
+
+class TestPairTabPreprocessUneven(unittest.TestCase):
+    @patch("numpy.loadtxt")
+    def setUp(self, mock_loadtxt) -> None:
+        file_path = "dummy_path"
+        mock_loadtxt.return_value = np.array(
+            [
+                [0.005, 1.0, 2.0, 3.0],
+                [0.01, 0.8, 1.6, 2.4],
+                [0.015, 0.5, 1.0, 1.5],
+                [0.02, 0.25, 0.4, 0.75],
+                [0.025, 0., 0.1, 0.],
+            ]
+        )
+
+        self.tab1 = PairTab(filename=file_path, rcut=0.025)
+        self.tab2 = PairTab(filename=file_path, rcut=0.028)
+        self.tab3 = PairTab(filename=file_path, rcut=0.03)
+
+
+    def test_preprocess(self):
+
+        np.testing.assert_allclose(self.tab1.vdata, np.array(
+            [
+                [0.005, 1.0, 2.0, 3.0],
+                [0.01, 0.8, 1.6, 2.4],
+                [0.015, 0.5, 1.0, 1.5],
+                [0.02, 0.25, 0.4, 0.75],
+                [0.025, 0., 0.1, 0.],
+                [0.03, 0.,  0.,  0.],
+            ]
+        ))
+        np.testing.assert_allclose(self.tab2.vdata, np.array(
+            [
+                [0.005, 1.0, 2.0, 3.0],
+                [0.01, 0.8, 1.6, 2.4],
+                [0.015, 0.5, 1.0, 1.5],
+                [0.02, 0.25, 0.4, 0.75],
+                [0.025, 0., 0.1, 0.],
+                [0.03, 0.,  0.,  0.],
+            ]
+        ))
+        np.testing.assert_allclose(self.tab3.vdata, np.array(
+            [
+                [0.005, 1.0, 2.0, 3.0],
+                [0.01, 0.8, 1.6, 2.4],
+                [0.015, 0.5, 1.0, 1.5],
+                [0.02, 0.25, 0.4, 0.75],
+                [0.025, 0., 0.1, 0.],
+                [0.03, 0., 0., 0.],
+                [0.035, 0., 0., 0.],
+            ]
+        ))
+
+        temp_data = self.tab3.tab_data.reshape(2,2,-1,4)
+
+        np.testing.assert_allclose(temp_data[0,0,-2:], np.zeros((2,4)))
+        np.testing.assert_allclose(temp_data[1,1,-2:], np.zeros((2,4)))
+        np.testing.assert_allclose(temp_data[0,1,-1:], np.zeros((1,4)))
+        np.testing.assert_allclose(temp_data[1,0,-1:], np.zeros((1,4)))
+